Hybrid Trajectory Planning Approach for Drone Networks

Drone networks have been recently utilized in a wide range of real-life applications due to their efficient feasibility in performing tasks with minimal cost and effort. However, the most frequent issue with drones is the energy consumption due to their limited battery life. Most of the efforts in the literature try to minimize the energy consumption and flying time. Moreover, obstacle avoidance is another issue for drones during operation. However, to overcome these issues, most of the methods in the literature are developed based on standard algorithms. Hence, this work suggested a novel approach for drone trajectory path planning that combines the concepts of spiral and boustrophedon algorithms. Also, concepts inspired by complex networks are involved in the proposed approach for modeling a real-life environment. The proposed approach is evaluated under different flying heights using metrics such as power and time consumption, coverage, and obstacle avoidance. The findings show that the proposed approach outperforms other standard algorithms in the literature.